- Course content
- Teaching staff
- Entry requirements
- Tuition fees and term dates
- Career opportunities
Intake: September only
Duration: 12 months full-time
Fees: £25,000 (full-time)
Financial support: Please see our Scholarships page
Application deadline: None - rolling admissions
Next Information Session: 11th January 2017
The Quant cluster of the Cass MSc programmes focuses on risk in its different facets such as identifying, modelling, measuring and managing it. You will gain essential knowledge and skills used in financial engineering, trading and quantitative analysis. This will help you to start a successful career in the financial industry.
These MSc courses will offer you a solid knowledge of financial theory and risk analysis, econometrics and stochastic processes, numerical analysis and programming languages, with special emphasis on valuation and risk management. These courses are rigorous with respect to the mathematics but also place great emphasis on linking theory with real world developments. You will often be exposed to the teaching by real world practitioners from the City of London.
The demand for recruits with strong quantitative skills has spread beyond the pure derivatives area, and graduates from the three quants courses move into a range of careers in the financial sector. Typical career paths include roles involving the development, management and improvements of pricing and hedging models, model validation, stress testing/scenario analysis, development and improvements of asset allocation models and analysis of potential investment vehicles across different asset classes as well as trading, sales and buy side.
Cass Business School proximity to the City of London helps graduates to access outstanding career opportunities, especially as the Business School has close links with many City institutions. Cass’s modern facilities include Bloomberg and Thomson Reuters trading terminals and numerous databases. Those terminals allow to simulate a trading environment and helps students to prepare them for a competitive real world.
- Quantitative Finance
- Mathematical Trading & Finance
- Financial Mathematics
The MSc in Quantitative Finance develops sophisticated statistical and econometrics skills for analyst roles in areas such as quantitative asset management and risk management. Special emphasis is on econometric techniques such as forecasting asset returns or volatility.
The MSc in Mathematical Trading & Finance prepares you employment opportunities in risk and working with instruments created by financial innovation.
The MSc in Financial Mathematics draws on tools from applied mathematics, computer science, statistics and economic theory to prepare you for roles in which you will combine in-depth knowledge of financial products and risk with sophisticated technical and programming skills.
All three courses contain a substantial amount of programming in Matlab and VBA.
Find out more, join us for an on-campus or online Information Session:
If you would like to arrange an individual appointment to discuss this programme please email Donna Coombs .
We review all our courses regularly to keep them up-to-date on issues of both theory and practice.
To satisfy the requirements of the degree course students must complete:
eight core courses (15 credits each)
two additional core modules plus three electives (10 credits each)
three electives (10 credits each) and an Applied Research Project (20 credits)
one elective (10 credits) and a Business Research Project (40 credits)
Assessment of modules on the MSc in Quantitative Finance, in most cases, is by means of coursework and unseen examination. Coursework may consist of standard essays, individual and group presentations, group reports, classwork, unseen tests and problem sets. Please note that any group work may include an element of peer assessment.
Two Induction Weeks The Quantitative Finance course starts with two compulsory induction weeks, focused on:
- an introduction to careers in finance and the opportunity to speak to representatives from over 75 companies during a number of different industry specific fairs.
- a reminder course of advanced financial mathematics, statistics and basic computing which forms a prerequisite of the core modules in term 1.
MSc Research Project
Students have the option of studying five specialised electives in term three to give them a breadth of subject matter. Alternatively if students would like to study one particular area of interest in depth they have the option of taking one elective and completing a Business Research Project, which in some cases may be completed in partnership with a sponsoring organisation.
The Project will be of approximately 8,000 words. This offers an opportunity to specialise in a contemporary finance topic related to students' future careers. The Project should be based on independent research either in the context of a single organisation or using third-party sources.
Students are encouraged from the start of the course to think about a topic for their Project. A member of academic staff supervises the project, and the student may choose whom they would like to work with. The Project must be submitted by the end of August. Company sponsored projects are encouraged and a number of such projects may be available.
Many students use this opportunity to complete a project in conjunction with an organisation they might want to work for. This gets their foot in the door and can lead to permanent employment post programme, whilst earning course credit. Cass Careers Service works to coordinate projects with organisations and students.
Some recent projects:
- Stock returns and volatility in Chinese stock markets
- Nearest neighbour estimators and foreign exchange rate predictions The inflation market of Sweden - an empirical investigation employing the Markov switching model
- Sovereign credit default swaps intensity calibration, estimation and application
- A comparative study of volatility forecasting models for the Greek stock market index
- Modelling and pricing credit index tranches using the normal inverse Gaussian distribution
- Fractional Co-integration and Long Memory in index options: Application to High Frequency statistical arbitrage trading strategies
- Relationship Between Default Values and Recovery Rates and its Effect on Portfolio Credit Risk
- Time Varying correlation between stock and bond returns
The teaching staff on the MSc in Quantitative Finance have many years of practical experience working in the financial services sector and are also active researchers in their fields.
This knowledge and experience inform the highly interactive lectures that make up the MSc in Quantitative Finance.
Other Module Leaders include:
- Prof. Keith Cuthbertson
- Prof. Giovanni Urga
- Dr Lorenzo Trapani
- Dr Laura Ballotta
- Dr Ioannis Kyriakou
- Dr Gianluca Fusai
- Dr Max Bruche
Teaching staff on Cass Talks
Some of the lecturing staff on the MSc in Quantitative Finance have taken part in recent editions of Cass Talks.
Dirk Nitzsche on Mutual Funds
Prof. Keith Cuthbertson on female quotas for boards
Cass Business School is among the global elite of business schools that hold the gold standard of 'triple-crown' accreditation from the Association to Advance Collegiate Schools of Business (AACSB), the Association of MBAs (AMBA) and the European Quality Improvement System (EQUIS). We are consistently ranked amongst the best business schools and programmes in the world which, coupled with an established 40-year reputation for excellence in research and business education, enables us to attract some of the best academics, students and businesses worldwide into our exclusive Cass network.
Documents required for decision-making
- Transcript/interim transcript
- Current module list if still studying
- Personal statement (500-600 words)
Documents which may follow at a later date
- IELTS result, if report available
- Confirmation of professional qualification examinations/exemptions/passes, if applicable
- Two references
- Work experience is not a requirement of this course
- For a successful application to receive an unconditional status all documents must be verified, so an original or certified copy of the degree transcript must be sent by post to Specialist Masters Programme Office, 106 Bunhill Row, London, EC1Y 8TZ, UK
We cannot comment on individual eligibility before you apply and we can only process your application once it is fully complete, with all requested information received.
The entry requirements for the MSc Quantitative Finance are as follows:
- A UK upper second class degree or above, or the equivalent from an overseas institution.
- Your academic background should be in a highly quantitative subject such as mathematics, physics, engineering, economics or computer science and having covered areas such as statistics, linear algebra and calculus
You may also be requested to provide a syllabus of specific modules undertaken during your studies, as part of the assessment process. This is not required at the point of submitting an application however and will only be requested by the admissions team if required as part of the assessment process.
Applicants will need to submit two references, one of which MUST be an academic reference.
- If you have been studying in the UK for the last three years it is unlikely that you will have to take the test
- If you have studied a 2+2 degree with just two years in the UK you will be required to provide IELTS results and possibly to resit the tests to meet our requirements.
The required IELTS level is an average of 7.0 with a minimum of 6.5 in the writing section and no less than 6.0 in any other section.
Please note that due to changes in the UKVI's list of SELTs we are no longer able to accept TOEFL as evidence of English language for students who require a CAS as of April 2014.
Work experience is not a requirement, but please provide details of relevant experience that might enhance your profile. This information will be included in your CV which is required with all applications.
Tuition fees and term dates
Tuition fees 2017/18
Application fee: Nil
Tuition fees: £25,000 (full-time) Currency Converter
We offer a tuition fee reduction of £2,000 to successful applicants for MSc Quantitative Finance if they finalise acceptance of their offer before 1 April 2017.
Deposit: £2,000 (paid within 1 month of receiving offer and non-refundable unless conditions of offer are not met)
First installment: Half fees less deposit (to be paid at registration)
Second installment: Half fees (paid in January following start of course)
Term dates 2017/18
In-Person Registration (all students must attend): Commences 18 September 2017
Compulsory Induction: 18 - 29 September 2017
2 October 2017 - 8 December 2017
Term I exams
8 January 2018 - 19 January 2018
22 January 2018 - 30 March 2018
Term II exams
23 April 2018 - 4 May 2018
7 May 2018 - 22 June 2018
Term III exams
2 July 2018 - 13 July 2018
Resit periodStudents who are required to resit an examination or invigilated test will do so in the period:
13 - 31 August 2018
Submission deadline for Business Research Project or Applied Research Project
1 September 2018
Official Course End Date
30 September 2018
Although investment and hedge funds remain the biggest users and innovators in quantitative finance, other financial sectors such as commercial banking, insurance and fund management are now keenly interested. Fund managers and hedge funds, for example, make extensive use of quantitative techniques to develop trading strategies, optimise portfolios and assess risk.
MSc in Quantitative Finance Employability
Our Graduate Destination Survey of the MSc in Quantitative Finance class of 2014 shows that 76.8% of graduates are now either in work (61.1%) or not job seeking as they are in further study, military service etc. (15.7%)
Some examples of where graduates from the MSc in Quantitative Finance class of 2014 are working are:
- Capita Asset Services - Analyst
- RBS - Graduate Risk Analyst
- Dong MeKong Construction Manufacture and Trading - Project Assistant
- nPOWER - Quant Risk Analyst
You can also view data from our Graduate Destination Survey (pdf) from 2014.